BankTechAsia 2021 - Technology Risk Management
Conference Agenda

BankTech Asia 2021 – Technology Risk Management Series is here causing a ruckus in the banking industry! Back for the 13th year, the conference is bringing together even more experts in risk to give the delegates a conference that they would not forget! Banks are now facing greater and more prominent threats from changes that are happening at light speed to the technological systems applicable to the banks. The risk department of banks are already increasing their investments into technology risk management, the practice of prioritizing, quantifying, and managing cyber threats and systems outages remains incredibly important to ensure their data and systems remain secure. Don’t miss out on the excitement to come at the 13th BankTech Asia 2021 – Technology Risk Management Series.

10:00am - 10:05am
Welcome Address

 

Ong Ron Nee, Former Country Head of Financial Crime Risk Assurance, Compliance Assurance, HSBC Malaysia

 

Mr. Selva Nagappan, Managing Director, BankTech Asia 2021

Financial sectors are fated to make the first step to mitigate ‘tsunami’ impacts in supporting the recovery planning of a country. Since late February 2020, the World Bank Group has been keeping a close eye and analyzing financial sector policy measures globally. With indebtedness at record levels, the tight interlinkages between sovereign, financial and corporate sectors may give rise to adverse feedback loops, especially in countries with weaker crisis management and corporate insolvency frameworks. Hear from the expert on:

  • Why every bank needs a recovery plan, especially in the current environment.
  • How banks can anticipate “cliff effects” from the end of government-sponsored programs to support businesses and borrowers and work them into their recovery plans.
  • How banks can “build back better” after the crest of the pandemic by fully embracing customers’ desire for digital banking accessed from anywhere.

 

Glenn Tasky, Director, Financial Stability and Supervision & Payment and Settlement Systems, The SEACEN Centre, Malaysia

KPMG has stated regulators are expecting financial institutions to reach great consistency and integration of the first and second lines of defence especially in their approach to prevent, detect and respond to the fraud risk banks come across. The banking and financial institution have access to vast amounts of data – everything from credit card spending data and payment networks, to patterns of visits to branches and mobile app usage. When it comes to retail banks, fraud protection is a big problem so understanding patterns by using data requires much greater levels of processing and compute power. This session highlights on:-

  • How to lower the percent of the fraud detection rate with deep learning and AI Deployment?
  • How deep learning could improve the probability predictions, identify higher percentages of fraud cases in the banking and financial institution and to reduce false alarm?
  • Artificial intelligence and machine learning analysis in a banking and financial ecosystem to recognize the technological techniques in terms of ethical inclination towards the customers data.

 

Dipanjan Bhattacharjee, Former Managing Director and Head of Credit Risk, Marcus by Goldman Sachs & Vice President of Credit, Revolut, United States of America

Models have the ability to create financial or non-financial risks and each has its own limitation. Understanding, testing, and managing model failures are the key focus of model risk management particularly model validation. Similarly, for machine learning models in the banking sector, particular attention is made on how to manage model fairness, explainability, robustness, and model change control. Model interpretability, in particular, is critical to evaluate the conceptual soundness of models, an important requirement for applications in highly regulated institutions such as banks. With neural networks (including Deep Learning) and proper architectural choices, it can be a self-explanatory model, an inherently interpretable model. Hear from the speaker as he highlights on machine learning explainability and robustness on data bias and the limitations by incorporating it to the banking system, how to develop fundamentally interpretable models, and banks rapid adoption of machine learning in current times.

 

Agus Sudjianto, Executive Vice President, Head of Corporate Model Risk, Wells Fargo, United States of America

The world has changed in a flash. However, one of the constants in the banking sector is the need for lenders to assess the credit risk of both the new applicants as well as the existing borrowers. With COVID’s scenario, credit scoring models in banks may need additional time to refresh the data from the origination of a loan to shape the loss outcomes that have been made. Reasonable adjustments to the banking credit scores should anticipate the risk of volatility and future uncertainty banks may face amidst the COVID-19 impact. With the help of business analytics, banks can evolve to adapt to the explosion of available data in the era of Big Data to assist in managing potential risk. This session discusses on:-

  • Interdependent between analytics and information technology in the banking sector and how one needs to support one another.
  • How intelligent analytics is to support the growth and stability of financial institutions and contribute to the country’s economic growth?
  • Challenges and opportunities in banking analytics during the current unprecedented situation surrounded with countless uncertainty.

Moderator:

 

Neil Bartlett, Former Senior Vice President Data and Analytics, Royal Bank of Canada

 

Panelists:

 

Agus Sudjianto, Executive Vice President, Head of Corporate Model Risk, Wells Fargo, United States of America

 

 

Sumit Gupta, Chief Risk Officer, YES Bank, India

 

 

Dipanjan Bhattacharjee, Former Managing Director and Head of Credit Risk, Marcus by Goldman Sachs & Vice President of Credit, Revolut, United States of America

12:25pm - 13:00pm
Luncheon Break

Research has stated regulators are expecting financial institutions to reach great consistency and integration of the first and second lines of defence especially the rapid growth in the criticality of data in the new economy and of protecting consumer rights using data analytics across banks. Banks facing the surge in “financial big data sets”, reflection of new and rapidly developing electronic footprints as well as large and growing financial, administrative, and commercial records amplified the focus on technologies such as artificial intelligence, and potential for algorithms to deliver unexplained outcomes, or to be biased for or against a specific population. This session will explore :-

  • Analysis in customer behaviour using data and machine learning within the banks infrastructure to detect ethical bias with technological techniques for vulnerable customers.
  • Monetary and financial market developments in line with central banks’ mandates for price stability and financial stability.
  • Risk on data aggregation, the depiction of responsibilities, controls, and safeguards for customer data when banks or financial institutions partner with third parties organizations.
  • Overseeing the banking system and broader financial system via big data analytics processing huge quantities of daily data.

 

David R. Hardoon, Senior Advisor, Data and Artificial Intelligence, UnionBank Philippines & Senior Advisor (Artificial Intelligence), Singapore’s Corrupt Investigation Practices Bureau (CPIB)

The pandemic has left no industry, economy or society untouched. The spread of COVID-19 has altered the ways of interaction – personal and professional, necessitating the redesigning of the control environment. As Banks modernize and automate processes, they need to balance service, cost, and resilience in their decisions. In this session, hear from the expert on

  • Is outsourcing going to become a core part of the new operating model?
  • What are the critical information security and operational risks that need to be thought through and mitigated?

 

Sumit Gupta, Chief Risk Officer, YES Bank, India

Even though the world is turning to technology in almost every industry, there are still questions creeping around concerning personal data online. Application for a digital banking license has been flooding the central bank in recent times. With plans to issue up to digital banking licenses real soon, Bank Negara has set eyes on narrowing it for the SME, micro-SME and B40 segments. Would this make them an easy target in getting their data breached due to the mortgages and loans taken? In this session, hear from the panelists on:-

  • The security of individuals in dealing with humanoids for verification details.
  • Will the tightness in the digital license holders’ firewall be enough to protect anonymous or untraceable data breaches?
  • Risk precautions by the future digital bankers to safeguard personal data.

Moderator:

 

Harish Bhonsle, Former Head of Financial Crime Threat Mitigation, HSBC Malaysia & Risk Management Consultant, AMC International Consulting Co. Ltd, Thailand

 

Panelists:

 

Dhananjaya Tambe, Former Deputy Managing Director & Chief Information Officer at State Bank of India

 

 

Dimitri Chichlo, Non-Executive Director, Ukreximbank, Switzerland & Ukraine

The world pandemic hasn’t made it easier leading to recessions and simultaneously a spike in instances of money laundering. In 2019, Bank Negara Malaysia (BNM) received 113,353 reports on suspicious transaction reports (STR), an increase of 30% from 2018 analysis. Financial institutions are still depending heavily on manual efforts to monitor anti-money laundering compliance due to the fact systems are still on the fence of being hacked by unwanted guests. Hear from the experts on:-

  • The solidity in implementing a limit on physical cash transactions to increase or decrease the possibility of laundering.
  • The system can easily be duped by criminals wanting to launder black money. Is there a possibility for trigger point traps to be incorporated in intercepting the attempt of money laundering?

Moderator:

 

Hakimi Harun, Head of Group Financial Intelligence Unit, Maybank Group, Malaysia

 

Panelists:

 

Neelima Fernandes, Regulatory Governance and Enforcement Officer – Chief Risk Office, Deutsche Bank, United Kingdom

 

Over the past few decades, financial crime has become a growing concern for governments and financial institutions around the world because it can lead to enormous monetary losses and damage to an organisation’s reputation. The loss of revenue through criminal acts can hamper societies’ economic development and even threaten their stability. Model risk management across financial institutions have impacted the ability of financial crimes to deploy or to adjust the models in identifying fraud or money laundering activities. Not only that, the increased use of artificial intelligence and machine learning has compounded the challenges and need for a strong partnership between both financial crimes analytics with model risk management. Hear from the expert on the increasingly important role of data and analytics in reducing the risk of fraud and financial crime and in helping banks meet regulatory requirements.

 

Neelima Fernandes, Regulatory Governance and Enforcement Officer – Chief Risk Office, Deutsche Bank, United Kingdom

Various research has proven time and time again that artificial intelligence could be responsible for reshaping the banking structure, capturing eloquently on banks opening their data and machine learning algorithms. This freedom will accelerate the accuracy of AI and provide the high-level governance measures. Sector regulators and industry bodies need the assistance to create oversight and technical guidance for responsible bias detection and mitigation in their individual sectors, adding context-specific detail to the existing cross-cutting guidance on data protection, and any new cross-cutting guidance within the banking sector. In her presentation, Janet will be focusing on the global risk framework for management of risk in AI in banking, covering all essential considerations including explainability, accountability, conduct, governance and fairness in the implementation.

 

Janet Adams, AI and Risk Expert, Former Head of Risk and Controls, SME, TSB Bank & Global Head of Conduct, CMB, HSBC, United Kingdom

16:30pm
End of BankTech Asia 2021 (Technology Risk Management) - Virtual Series

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TECHNOLOGY RISK MANAGEMENT SERIES


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